dify
Production-ready platform for agentic workflow development.
Avoid common LLM application development pitfalls with Dify. Learn to fix schema mismatches, streaming errors, blocking code, and stale RAG data for smoother development. Improve your LLM projects now.
How Dify Implements ReAct-Based Agents: A Deep Dive into the Source CodeExplore how Dify implements ReAct-based agents. Dive into the source code of CotAgentRunner to understand the stateful streaming loop, tool execution, and observation feedback driving ReAct agent logic.
How to Build LLM Function Calling Agents in Dify: A Complete Technical GuideMaster LLM function calling agents in Dify with this technical guide. Learn the reusable pattern using FunctionCallAgentRunner to build powerful, iterative agents.
How Celery is Configured with Redis as a Broker in DifyLearn how Dify configures Celery with Redis as a broker. Discover how environment variables like CELERY_BROKER_URL and SSL options are used for efficient task management.
How Dify Implements Domain-Driven Design: Layered Architecture and Code PatternsDiscover how Dify implements Domain-Driven Design using a layered architecture. Explore entity isolation, service orchestration, and strict dependency rules for cleaner code.
What Is Flask in Dify's API Architecture? A Deep Dive into the Backend FoundationDiscover Flasks role in Dify API architecture. Learn how this WSGI framework handles routing extensions and powers the RESTful API backend.
Core Components of Dify's Agent Service: Architecture and Implementation GuideExplore Dify's agent service core components: API services, workflow nodes, and agent runners. Understand the architecture and implementation for reactive CoT reasoning with tool integration.
How Dify's Model Provider Management Service Works InternallyDiscover how Dify's model provider management service works internally. Learn about its two layer architecture, secure in-memory configurations, and data aggregation.
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